1. Field of the Invention
The present invention relates to an apparatus and method for generating a noise adaptive acoustic model for environment migration including a noise adaptive discriminative adaptation method.
The present invention is derived from a project entitled “Development of Large-Capacity Dialogic Distributed Processing Speech Interface for R&D Industry [2006-S-036-02]” conducted as an IT R&D program for the Ministry of Information and Communication (Republic of Korea).
2. Discussion of Related Art
One of the most important factors in a speech recognition technique is to efficiently remove noise caused by an environment. A discrepancy due to environment migration between a training environment and an actual speech recognition environment, which is caused by noise or channel distortion generated by an environment) is one of main factors that deteriorate performance of a commonly used speech recognizer.
In order to enable speech recognition environment migration in the discrepancy between environments, algorithms have been suggested to overcome the discrepancy between environments. Conventionally, noise is estimated at a signal level to be removed, so that a clear speech signal can be obtained, speech that is collected from various noise environments is used to train an acoustic model and a conventional acoustic model is adapted to an actual environment using a small quantity of speech data collected from an actually adapted environment.
However, there still exist drawbacks in the conventionally suggested methods.